{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 十四款常规机器学习建模\n",
    "\n",
    "参考案例一：[module-sklearn.ensemble](http://scikit-learn.org/stable/modules/classes.html#module-sklearn.ensemble)\n",
    "\n",
    "参考案例二：[ensemble-plot-feature-transformation](http://scikit-learn.org/stable/auto_examples/ensemble/plot_feature_transformation.html#sphx-glr-auto-examples-ensemble-plot-feature-transformation-py)\n",
    "\n",
    "\n",
    "练习步骤为：\n",
    "\n",
    "- 1、随机准备数据make_classification\n",
    "- 2、两套模型的训练与基本信息准备\n",
    "- 3、观察14套模型的准确率与召回率\n",
    "- 4、刻画14套模型的calibration plots校准曲线\n",
    "- 5、14套模型的重要性输出\n",
    "- 6、14套模型的ROC值计算与plot\n",
    "- 7、加权模型融合数据准备\n",
    "- 8、基准优化策略：14套模型融合——平均\n",
    "- 9、加权平均优化策略：14套模型融合——加权平均优化\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1、随机准备数据make_classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Automatically created module for IPython interactive environment\n",
      "(6400, 20) (2000, 20) (6400,) (2000,)\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.random.seed(10)\n",
    "%matplotlib inline \n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from sklearn.datasets import make_classification\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import (RandomTreesEmbedding, RandomForestClassifier,\n",
    "                              GradientBoostingClassifier)\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import roc_curve,accuracy_score,recall_score\n",
    "from sklearn.pipeline import make_pipeline\n",
    "from sklearn.calibration import calibration_curve\n",
    "import copy\n",
    "print(__doc__)\n",
    "from matplotlib.colors import ListedColormap\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.datasets import make_moons, make_circles, make_classification\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.gaussian_process import GaussianProcessClassifier\n",
    "from sklearn.gaussian_process.kernels import RBF\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis\n",
    "\n",
    "def yLabel(y_pred):\n",
    "    y_pred_f = copy.copy(y_pred)\n",
    "    y_pred_f[y_pred_f>=0.5] = 1\n",
    "    y_pred_f[y_pred_f<0.5] = 0\n",
    "    return y_pred_f\n",
    "\n",
    "def acc_recall(y_test, y_pred_rf):\n",
    "    return {'accuracy': accuracy_score(y_test, yLabel(y_pred_rf)), \\\n",
    "            'recall': recall_score(y_test, yLabel(y_pred_rf))}\n",
    "\n",
    "# 数据制作\n",
    "X, y = make_classification(n_samples=10000)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,random_state = 4000)  # 对半分\n",
    "X_train, X_train_lr, y_train, y_train_lr = train_test_split(X_train,\n",
    "                                                            y_train,\n",
    "                                                            test_size=0.2,random_state = 4000)\n",
    "\n",
    "print(X_train.shape, X_test.shape, y_train.shape, y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.1 八款主流机器学习模型\n",
    "\n",
    "参考 [classifier-comparison](http://scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html#sphx-glr-auto-examples-classification-plot-classifier-comparison-py)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Start Model : Nearest Neighbors ----\n",
      "\n",
      "CPU times: user 7.21 ms, sys: 0 ns, total: 7.21 ms\n",
      "Wall time: 6.45 ms\n",
      "CPU times: user 594 ms, sys: 0 ns, total: 594 ms\n",
      "Wall time: 523 ms\n",
      "\n",
      " --- Start Model : Linear SVM ----\n",
      "\n",
      "CPU times: user 524 ms, sys: 0 ns, total: 524 ms\n",
      "Wall time: 522 ms\n",
      "CPU times: user 80.9 ms, sys: 0 ns, total: 80.9 ms\n",
      "Wall time: 80.5 ms\n",
      "\n",
      " --- Start Model : RBF SVM ----\n",
      "\n",
      "CPU times: user 4.16 s, sys: 94.3 ms, total: 4.25 s\n",
      "Wall time: 4.15 s\n",
      "CPU times: user 720 ms, sys: 0 ns, total: 720 ms\n",
      "Wall time: 719 ms\n",
      "\n",
      " --- Start Model : Decision Tree ----\n",
      "\n",
      "CPU times: user 74.4 ms, sys: 0 ns, total: 74.4 ms\n",
      "Wall time: 74.2 ms\n",
      "CPU times: user 627 µs, sys: 0 ns, total: 627 µs\n",
      "Wall time: 554 µs\n",
      "\n",
      " --- Start Model : Neural Net ----\n",
      "\n",
      "CPU times: user 1.78 s, sys: 967 ms, total: 2.75 s\n",
      "Wall time: 1.38 s\n",
      "CPU times: user 3.18 ms, sys: 5.37 ms, total: 8.55 ms\n",
      "Wall time: 4.28 ms\n",
      "\n",
      " --- Start Model : AdaBoost ----\n",
      "\n",
      "CPU times: user 1 s, sys: 90.4 ms, total: 1.09 s\n",
      "Wall time: 988 ms\n",
      "CPU times: user 16.4 ms, sys: 0 ns, total: 16.4 ms\n",
      "Wall time: 16.2 ms\n",
      "\n",
      " --- Start Model : Naive Bayes ----\n",
      "\n",
      "CPU times: user 5.21 ms, sys: 0 ns, total: 5.21 ms\n",
      "Wall time: 5.03 ms\n",
      "CPU times: user 2.6 ms, sys: 0 ns, total: 2.6 ms\n",
      "Wall time: 2.47 ms\n",
      "\n",
      " --- Start Model : QDA ----\n",
      "\n",
      "CPU times: user 19.4 ms, sys: 0 ns, total: 19.4 ms\n",
      "Wall time: 11.4 ms\n",
      "CPU times: user 3.78 ms, sys: 0 ns, total: 3.78 ms\n",
      "Wall time: 1.9 ms\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/sklearn/discriminant_analysis.py:682: UserWarning: Variables are collinear\n",
      "  warnings.warn(\"Variables are collinear\")\n"
     ]
    }
   ],
   "source": [
    "\n",
    "h = .02  # step size in the mesh\n",
    "names = [\"Nearest Neighbors\", \"Linear SVM\", \"RBF SVM\",\n",
    "         \"Decision Tree\", \"Neural Net\", \"AdaBoost\",\n",
    "         \"Naive Bayes\", \"QDA\"]\n",
    "# 去掉\"Gaussian Process\"，太耗时，是其他的300倍以上\n",
    "\n",
    "classifiers = [\n",
    "    KNeighborsClassifier(3),\n",
    "    SVC(kernel=\"linear\", C=0.025),\n",
    "    SVC(gamma=2, C=1),\n",
    "    #GaussianProcessClassifier(1.0 * RBF(1.0)),\n",
    "    DecisionTreeClassifier(max_depth=5),\n",
    "    #RandomForestClassifier(max_depth=5, n_estimators=10, max_features=1),\n",
    "    MLPClassifier(alpha=1),\n",
    "    AdaBoostClassifier(),\n",
    "    GaussianNB(),\n",
    "    QuadraticDiscriminantAnalysis()]\n",
    "\n",
    "predictEight = {}\n",
    "for name, clf in zip(names, classifiers):\n",
    "    predictEight[name] = {}\n",
    "    predictEight[name]['prob_pos'],predictEight[name]['fpr_tpr'],predictEight[name]['acc_recall'] = [],[],[]\n",
    "    predictEight[name]['importance'] = []\n",
    "    print('\\n --- Start Model : %s ----\\n'%name)\n",
    "    %time clf.fit(X_train, y_train)\n",
    "    # Plot the decision boundary. For that, we will assign a color to each\n",
    "    # point in the mesh [x_min, x_max]x[y_min, y_max].\n",
    "    if hasattr(clf, \"decision_function\"):\n",
    "        %time prob_pos = clf.decision_function(X_test)\n",
    "        # # The confidence score for a sample is the signed distance of that sample to the hyperplane.\n",
    "    else:\n",
    "        %time prob_pos= clf.predict_proba(X_test)[:, 1]\n",
    "        prob_pos = (prob_pos - prob_pos.min()) / (prob_pos.max() - prob_pos.min())\n",
    "        # 需要归一化\n",
    "    predictEight[name]['prob_pos'] = prob_pos\n",
    "    \n",
    "    # 计算ROC、acc、recall\n",
    "    predictEight[name]['fpr_tpr'] = roc_curve(y_test, prob_pos)[:2]\n",
    "    predictEight[name]['acc_recall'] = acc_recall(y_test, prob_pos)  # 计算准确率与召回\n",
    "    \n",
    "    # 提取重要性信息\n",
    "    if hasattr(clf, \"coef_\"):\n",
    "        predictEight[name]['importance'] = clf.coef_\n",
    "    elif hasattr(clf, \"feature_importances_\"):\n",
    "        predictEight[name]['importance'] = clf.feature_importances_\n",
    "    elif hasattr(clf, \"sigma_\"):\n",
    "        predictEight[name]['importance'] = clf.sigma_\n",
    "        # variance of each feature per class"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2 组合模型延伸\n",
    "\n",
    "参考官网[feature-transformation](http://scikit-learn.org/stable/auto_examples/ensemble/plot_feature_transformation.html#sphx-glr-auto-examples-ensemble-plot-feature-transformation-py)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LM 开始计算...\n",
      "CPU times: user 18.5 ms, sys: 936 µs, total: 19.5 ms\n",
      "Wall time: 18.2 ms\n",
      "随机森林编码+LM 开始计算...\n",
      "CPU times: user 619 ms, sys: 95.5 ms, total: 714 ms\n",
      "Wall time: 610 ms\n",
      "\n",
      " 随机森林系列 开始计算... \n",
      "CPU times: user 84.5 ms, sys: 0 ns, total: 84.5 ms\n",
      "Wall time: 84.5 ms\n",
      "\n",
      " 梯度提升树系列 开始计算... \n",
      "CPU times: user 60.8 ms, sys: 1.69 ms, total: 62.4 ms\n",
      "Wall time: 62.5 ms\n"
     ]
    }
   ],
   "source": [
    "n_estimator = 100\n",
    "\n",
    "'''\n",
    "model 0 : lm\n",
    "logistic\n",
    "'''\n",
    "print('LM 开始计算...')\n",
    "lm = LogisticRegression()\n",
    "%time lm.fit(X_train, y_train)\n",
    "y_pred_lm = lm.predict_proba(X_test)[:, 1]\n",
    "fpr_lm, tpr_lm, _ = roc_curve(y_test, y_pred_lm)\n",
    "lm_ar = acc_recall(y_test, y_pred_lm)  # 计算准确率与召回\n",
    "\n",
    "'''\n",
    "model 1 : rt + lm\n",
    "无监督变换 + lg\n",
    "'''\n",
    "# Unsupervised transformation based on totally random trees\n",
    "print('随机森林编码+LM 开始计算...')\n",
    "rt = RandomTreesEmbedding(max_depth=3, n_estimators=n_estimator,\n",
    "    random_state=0)\n",
    "# 数据集的无监督变换到高维稀疏表示。\n",
    "\n",
    "rt_lm = LogisticRegression()\n",
    "pipeline = make_pipeline(rt, rt_lm)\n",
    "%time pipeline.fit(X_train, y_train)\n",
    "y_pred_rt = pipeline.predict_proba(X_test)[:, 1]\n",
    "fpr_rt_lm, tpr_rt_lm, _ = roc_curve(y_test, y_pred_rt)\n",
    "rt_lm_ar = acc_recall(y_test, y_pred_rt)  # 计算准确率与召回\n",
    "\n",
    "'''\n",
    "model 2 : RF / RF+LM\n",
    "'''\n",
    "print('\\n 随机森林系列 开始计算... ')\n",
    "# Supervised transformation based on random forests\n",
    "rf = RandomForestClassifier(max_depth=3, n_estimators=n_estimator)\n",
    "rf_enc = OneHotEncoder()\n",
    "rf_lm = LogisticRegression()\n",
    "rf.fit(X_train, y_train)\n",
    "rf_enc.fit(rf.apply(X_train))  # rf.apply(X_train)-(1310, 100)     X_train-(1310, 20)\n",
    "# 用100棵树的信息作为X，载入做LM模型\n",
    "%time rf_lm.fit(rf_enc.transform(rf.apply(X_train_lr)), y_train_lr)\n",
    "y_pred_rf_lm = rf_lm.predict_proba(rf_enc.transform(rf.apply(X_test)))[:, 1]\n",
    "fpr_rf_lm, tpr_rf_lm, _ = roc_curve(y_test, y_pred_rf_lm)\n",
    "rf_lm_ar = acc_recall(y_test, y_pred_rf_lm)  # 计算准确率与召回\n",
    "\n",
    "'''\n",
    "model 2 : GRD / GRD + LM\n",
    "'''\n",
    "print('\\n 梯度提升树系列 开始计算... ')\n",
    "grd = GradientBoostingClassifier(n_estimators=n_estimator)\n",
    "grd_enc = OneHotEncoder()\n",
    "grd_lm = LogisticRegression()\n",
    "grd.fit(X_train, y_train)\n",
    "grd_enc.fit(grd.apply(X_train)[:, :, 0])\n",
    "%time grd_lm.fit(grd_enc.transform(grd.apply(X_train_lr)[:, :, 0]), y_train_lr)\n",
    "\n",
    "y_pred_grd_lm = grd_lm.predict_proba(\n",
    "    grd_enc.transform(grd.apply(X_test)[:, :, 0]))[:, 1]\n",
    "fpr_grd_lm, tpr_grd_lm, _ = roc_curve(y_test, y_pred_grd_lm)\n",
    "grd_lm_ar = acc_recall(y_test, y_pred_grd_lm)  # 计算准确率与召回\n",
    "\n",
    "# The gradient boosted model by itself\n",
    "y_pred_grd = grd.predict_proba(X_test)[:, 1]\n",
    "fpr_grd, tpr_grd, _ = roc_curve(y_test, y_pred_grd)\n",
    "grd_ar = acc_recall(y_test, y_pred_grd)  # 计算准确率与召回\n",
    "\n",
    "# The random forest model by itself\n",
    "y_pred_rf = rf.predict_proba(X_test)[:, 1]\n",
    "fpr_rf, tpr_rf, _ = roc_curve(y_test, y_pred_rf)\n",
    "rf_ar = acc_recall(y_test, y_pred_rf)  # 计算准确率与召回"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3、观察14套模型的准确率与召回率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----- 第一套,8款常规机器学习模型 -----\n",
      "\n",
      " ----- The Model  : Decision Tree , -----\n",
      " \n",
      "{'recall': 0.90918264379414737, 'accuracy': 0.89949999999999997}\n",
      "\n",
      " ----- The Model  : Nearest Neighbors , -----\n",
      " \n",
      "{'recall': 0.8446014127144299, 'accuracy': 0.83150000000000002}\n",
      "\n",
      " ----- The Model  : QDA , -----\n",
      " \n",
      "{'recall': 0.8446014127144299, 'accuracy': 0.8155}\n",
      "\n",
      " ----- The Model  : Neural Net , -----\n",
      " \n",
      "{'recall': 0.91321897073662972, 'accuracy': 0.90049999999999997}\n",
      "\n",
      " ----- The Model  : Linear SVM , -----\n",
      " \n",
      "{'recall': 0.84561049445005043, 'accuracy': 0.89100000000000001}\n",
      "\n",
      " ----- The Model  : AdaBoost , -----\n",
      " \n",
      "{'recall': 0.028254288597376387, 'accuracy': 0.51800000000000002}\n",
      "\n",
      " ----- The Model  : RBF SVM , -----\n",
      " \n",
      "{'recall': 0.0, 'accuracy': 0.50449999999999995}\n",
      "\n",
      " ----- The Model  : Naive Bayes , -----\n",
      " \n",
      "{'recall': 0.91523713420787078, 'accuracy': 0.89300000000000002}\n",
      "----- 第二套,6款组合机器学习模型 -----\n",
      "\n",
      " --- LM 准确率与召回为: ---- \n",
      "  {'recall': 0.91523713420787078, 'accuracy': 0.90049999999999997}\n",
      "\n",
      " --- LM + RT 准确率与召回为: ---- \n",
      "  {'recall': 0.87689202825428858, 'accuracy': 0.89200000000000002}\n",
      "\n",
      " --- LM + RF 准确率与召回为: ---- \n",
      "  {'recall': 0.89404641775983851, 'accuracy': 0.88800000000000001}\n",
      "\n",
      " --- GBT + LM 准确率与召回为: ---- \n",
      "  {'recall': 0.89606458123107968, 'accuracy': 0.88949999999999996}\n",
      "\n",
      " --- GBT 准确率与召回为: ---- \n",
      "  {'recall': 0.90615539858728555, 'accuracy': 0.89900000000000002}\n",
      "\n",
      " --- RF 准确率与召回为: ---- \n",
      "  {'recall': 0.8990918264379415, 'accuracy': 0.90249999999999997}\n"
     ]
    }
   ],
   "source": [
    "print('----- 第一套,8款常规机器学习模型 -----')\n",
    "for x,y in predictEight.items():\n",
    "    print('\\n ----- The Model  : %s , -----\\n '%(x)  )\n",
    "    print(predictEight[x]['acc_recall'])\n",
    "\n",
    "print('\\n ----- 第二套,6款组合机器学习模型 -----\\n ')\n",
    "names = ['LM','LM + RT','LM + RF','GBT + LM','GBT','RF']\n",
    "ar_list = [lm_ar,rt_lm_ar,rf_lm_ar,grd_lm_ar,grd_ar,rf_ar]\n",
    "for x,y in zip(names,ar_list):\n",
    "    print('\\n --- %s 准确率与召回为: ---- \\n '%x,y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4、刻画14套模型的calibration plots校准曲线\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# #############################################################################\n",
    "# Plot calibration plots\n",
    "names = [\"Nearest Neighbors\", \"Linear SVM\", \"RBF SVM\",\n",
    "         \"Decision Tree\", \"Neural Net\", \"AdaBoost\",\n",
    "         \"Naive Bayes\", \"QDA\"]\n",
    "\n",
    "plt.figure(figsize=(15, 15))\n",
    "ax1 = plt.subplot2grid((3, 1), (0, 0), rowspan=2)\n",
    "ax2 = plt.subplot2grid((3, 1), (2, 0))\n",
    "\n",
    "ax1.plot([0, 1], [0, 1], \"k:\", label=\"Perfectly calibrated\")\n",
    "for prob_pos, name in [[predictEight[n]['prob_pos'],n] for n in names] + [(y_pred_lm,'LM'),\n",
    "                       (y_pred_rt,'RT + LM'),\n",
    "                       (y_pred_rf_lm,'RF + LM'),\n",
    "                       (y_pred_grd_lm,'GBT + LM'),\n",
    "                       (y_pred_grd,'GBT'),\n",
    "                       (y_pred_rf,'RF')]:\n",
    "    \n",
    "    prob_pos = (prob_pos - prob_pos.min()) / (prob_pos.max() - prob_pos.min())\n",
    "        \n",
    "    fraction_of_positives, mean_predicted_value = calibration_curve(y_test, prob_pos, n_bins=10)\n",
    "\n",
    "    ax1.plot(mean_predicted_value, fraction_of_positives, \"s-\",\n",
    "             label=\"%s\" % (name, ))\n",
    "\n",
    "    ax2.hist(prob_pos, range=(0, 1), bins=10, label=name,\n",
    "             histtype=\"step\", lw=2)\n",
    "\n",
    "ax1.set_ylabel(\"Fraction of positives\")\n",
    "ax1.set_ylim([-0.05, 1.05])\n",
    "ax1.legend(loc=\"lower right\")\n",
    "ax1.set_title('Calibration plots  (reliability curve)')\n",
    "\n",
    "ax2.set_xlabel(\"Mean predicted value\")\n",
    "ax2.set_ylabel(\"Count\")\n",
    "ax2.legend(loc=\"upper center\", ncol=2)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5、14套模型的重要性输出\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " -------- RadomFree importances ------------\n",
      "\n",
      "[ 0.00550889  0.0013416   0.00946843  0.00315386  0.00159297  0.06351259\n",
      "  0.00481246  0.00261838  0.00334271  0.00819454  0.00222307  0.07692323\n",
      "  0.00181319  0.00345627  0.00372946  0.28387983  0.00550478  0.00504261\n",
      "  0.51273344  0.0011477 ]\n",
      "\n",
      " -------- GradientBoosting importances ------------\n",
      "\n",
      "[ 0.02152663  0.03314941  0.04194018  0.03530701  0.03252671  0.0292791\n",
      "  0.02210118  0.03490943  0.04569092  0.02321902  0.01988773  0.03633324\n",
      "  0.03463489  0.03635186  0.02302306  0.0666606   0.02946956  0.02633897\n",
      "  0.38243275  0.02521775]\n",
      "\n",
      " -------- Logistic Coefficient  ------------\n",
      "\n",
      "[[-0.04287553 -0.036421   -0.04945902  0.13253335  0.02649143 -0.17965617\n",
      "  -0.00579479 -0.00512973  0.01951769 -0.02659169 -0.06579998 -0.49465367\n",
      "   0.02783032 -0.09474882 -0.03196817  0.97077326  0.10568118  0.06478186\n",
      "   2.33393955 -0.05842173]]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/ipykernel_launcher.py:12: DeprecationWarning: elementwise != comparison failed; this will raise an error in the future.\n",
      "  if sys.path[0] == '':\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[array([  2.09875561e-03,   0.00000000e+00,   1.25998010e-03,\n",
       "           0.00000000e+00,   7.28734587e-04,   1.89254296e-02,\n",
       "           1.31368357e-03,   1.01971475e-03,   3.11957777e-03,\n",
       "           0.00000000e+00,   0.00000000e+00,   1.24014043e-03,\n",
       "           2.29969029e-03,   0.00000000e+00,   1.06086399e-03,\n",
       "           5.01131094e-03,   2.01052164e-03,   9.20372735e-04,\n",
       "           9.58991224e-01,   0.00000000e+00]), 'Decision Tree'],\n",
       " [array([[-0.01216941, -0.00803642, -0.0371962 ,  0.0440979 ,  0.02813782,\n",
       "          -0.11937585, -0.01560251,  0.00472539,  0.00288186, -0.02019184,\n",
       "          -0.03446023, -0.3192126 ,  0.01783739, -0.03038167, -0.03201148,\n",
       "           0.5766335 ,  0.0523026 ,  0.0390042 ,  1.41965647, -0.02905152]]),\n",
       "  'Linear SVM'],\n",
       " [array([ 0.02,  0.06,  0.08,  0.02,  0.  ,  0.04,  0.04,  0.  ,  0.02,\n",
       "          0.04,  0.  ,  0.1 ,  0.  ,  0.04,  0.  ,  0.18,  0.04,  0.02,\n",
       "          0.3 ,  0.  ]), 'AdaBoost'],\n",
       " [array([[ 0.99215286,  1.00848734,  1.06211506,  1.0240741 ,  0.98769432,\n",
       "           0.4869747 ,  1.02797477,  1.01967028,  0.95005496,  0.93633662,\n",
       "           0.99736016,  1.60130181,  1.00589126,  0.97670992,  1.01558554,\n",
       "           1.20659868,  1.00973942,  0.99938876,  0.89444533,  0.97622153],\n",
       "         [ 1.03603107,  1.03187653,  0.96780999,  0.96882558,  0.96528512,\n",
       "           0.43647263,  1.01035563,  1.01598846,  0.9969073 ,  1.00241327,\n",
       "           0.99849963,  1.43008874,  0.97184961,  1.02087461,  0.9725773 ,\n",
       "           1.00687468,  1.00999682,  0.99485187,  0.45987268,  1.00623763]]),\n",
       "  'Naive Bayes']]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 重要性\n",
    "print('\\n -------- RadomFree importances ------------\\n')\n",
    "print(rf.feature_importances_)\n",
    "print('\\n -------- GradientBoosting importances ------------\\n')\n",
    "print(grd.feature_importances_)\n",
    "print('\\n -------- Logistic Coefficient  ------------\\n')\n",
    "print(lm.coef_ )\n",
    "\n",
    "\n",
    "# 其他几款模型的特征选择\n",
    "eight_names = list(predictEight.keys())\n",
    "[[predictEight[n]['importance'],n] for n in eight_names if predictEight[n]['importance'] != [] ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6、14套模型的ROC值计算与plot\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEWCAYAAACJ0YulAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff61ee60d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEWCAYAAABIVsEJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTl64AXEcx3Hy4n8wdKEr84MO4wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff61ee43048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(1)\n",
    "plt.plot([0, 1], [0, 1], 'k--')\n",
    "plt.plot(fpr_lm, tpr_lm, label='LR')\n",
    "plt.plot(fpr_rt_lm, tpr_rt_lm, label='RT + LR')\n",
    "plt.plot(fpr_rf, tpr_rf, label='RF')\n",
    "plt.plot(fpr_rf_lm, tpr_rf_lm, label='RF + LR')\n",
    "plt.plot(fpr_grd, tpr_grd, label='GBT')\n",
    "plt.plot(fpr_grd_lm, tpr_grd_lm, label='GBT + LR')\n",
    "# 8 款模型\n",
    "for (fpr,tpr),name in [[predictEight[n]['fpr_tpr'],n] for n in eight_names] :\n",
    "    plt.plot(fpr, tpr, label=name)\n",
    "    \n",
    "\n",
    "plt.xlabel('False positive rate')\n",
    "plt.ylabel('True positive rate')\n",
    "plt.title('ROC curve')\n",
    "plt.legend(loc='best')\n",
    "plt.show()\n",
    "\n",
    "plt.figure(2)\n",
    "plt.xlim(0, 0.2)\n",
    "plt.ylim(0.4, 1)     # ylim改变     # matt\n",
    "plt.plot([0, 1], [0, 1], 'k--')\n",
    "plt.plot(fpr_lm, tpr_lm, label='LR')\n",
    "plt.plot(fpr_rt_lm, tpr_rt_lm, label='RT + LR')\n",
    "plt.plot(fpr_rf, tpr_rf, label='RF')\n",
    "plt.plot(fpr_rf_lm, tpr_rf_lm, label='RF + LR')\n",
    "plt.plot(fpr_grd, tpr_grd, label='GBT')\n",
    "plt.plot(fpr_grd_lm, tpr_grd_lm, label='GBT + LR')\n",
    "for (fpr,tpr),name in [[predictEight[n]['fpr_tpr'],n] for n in eight_names] :\n",
    "    plt.plot(fpr, tpr, label=name)\n",
    "plt.xlabel('False positive rate')\n",
    "plt.ylabel('True positive rate')\n",
    "plt.title('ROC curve (zoomed in at top left)')\n",
    "plt.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## optimize\n",
    "\n",
    "    借助快照集成，参考：(titu1994/Snapshot-Ensembles)[https://github.com/titu1994/Snapshot-Ensembles]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7、加权模型融合数据准备\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from MinimiseOptimize import MinimiseOptimize,log_loss_func,calculate_weighted_accuracy\n",
    "\n",
    "# 集成数据准备\n",
    "preds_dict = {}\n",
    "for pred_tmp,name in [[predictEight[n]['prob_pos'],n] for n in names] + [(y_pred_lm,'LM'),\n",
    "                       (y_pred_rt,'RT + LM'),\n",
    "                       (y_pred_rf_lm,'RF + LM'),\n",
    "                       (y_pred_grd_lm,'GBT + LM'),\n",
    "                       (y_pred_grd,'GBT'),\n",
    "                       (y_pred_rf,'RF')]:\n",
    "    preds_dict[name] = np.array([1 - pred_tmp , pred_tmp]).T\n",
    "\n",
    "# 参数准备\n",
    "preds = list(preds_dict.values())\n",
    "models_filenames = list(preds_dict.keys())  # 模型个数\n",
    "sample_N,nb_classes = preds[0].shape  # 样本数/分类数\n",
    "testY = y_test.reshape((len(y_test),1))  # 真实Label (2000,1)\n",
    "testY_cat = np.array([1 - y_test ,y_test]).T # (2000,2)   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8、基准优化策略：14套模型融合——平均\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy :  79.7\n",
      "Recall :  0.7043390514631686\n"
     ]
    }
   ],
   "source": [
    "# 模型集成：无权重\n",
    "    # 无权重则代表权重为平均值\n",
    "prediction_weights = [1. / len(models_filenames)] * len(models_filenames)\n",
    "calculate_weighted_accuracy(prediction_weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 9、加权平均优化策略：14套模型融合——加权平均优化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " ------- Iteration : 1  - acc: 89.9  - rec:0.917255297679112 -------  \n",
      "    Best Ensemble Weights: \n",
      " [6.01413708e-02 1.67765866e-01 2.18761400e-01 1.37602260e-01\n",
      " 3.79936007e-08 1.64447752e-15 0.00000000e+00 1.18466862e-01\n",
      " 6.99878403e-03 1.29796869e-02 2.77283733e-01 6.11475028e-17\n",
      " 6.82844127e-17 2.23356528e-21]\n",
      "\n",
      " ------- Iteration : 2  - acc: 89.4  - rec:0.9031281533804238 -------  \n",
      "    Best Ensemble Weights: \n",
      " [6.16594671e-01 1.09796545e-16 4.86993420e-17 7.15898170e-04\n",
      " 7.02153751e-03 4.06538875e-02 2.92130834e-16 5.85976713e-02\n",
      " 3.25680485e-17 1.04785370e-03 9.85813768e-02 8.48198215e-04\n",
      " 1.75420590e-01 5.18315324e-04]\n",
      "\n",
      " ------- Iteration : 3  - acc: 90.3  - rec:0.9112008072653885 -------  \n",
      "    Best Ensemble Weights: \n",
      " [1.65963646e-02 8.35407374e-02 1.07596623e-01 2.01735336e-05\n",
      " 0.00000000e+00 1.79786622e-05 6.15720544e-20 2.59754148e-21\n",
      " 1.82768751e-01 1.24355235e-03 1.72258605e-01 2.38942641e-04\n",
      " 4.35718271e-01 7.54761612e-20]\n",
      "\n",
      " ------- Iteration : 4  - acc: 89.35  - rec:0.9182643794147326 -------  \n",
      "    Best Ensemble Weights: \n",
      " [2.52703712e-01 6.81759656e-20 0.00000000e+00 3.53327625e-02\n",
      " 1.14932524e-16 3.76067423e-19 1.97197148e-19 2.98319254e-01\n",
      " 8.00245331e-17 4.48124265e-06 4.13639790e-01 1.87330342e-16\n",
      " 4.78697909e-19 1.11179180e-16]\n",
      "\n",
      " ------- Iteration : 5  - acc: 89.7  - rec:0.9142280524722503 -------  \n",
      "    Best Ensemble Weights: \n",
      " [8.18990818e-02 3.93542361e-04 8.66904160e-04 2.11910480e-16\n",
      " 7.83256171e-03 3.61921242e-06 1.76245915e-01 1.44180369e-01\n",
      " 1.62241529e-01 5.41996713e-18 4.02083972e-01 2.95034060e-04\n",
      " 2.39277251e-02 2.97456021e-05]\n",
      "\n",
      " ------- Iteration : 6  - acc: 89.8  - rec:0.9081735620585267 -------  \n",
      "    Best Ensemble Weights: \n",
      " [1.91058562e-01 0.00000000e+00 1.41352097e-01 5.19749363e-03\n",
      " 7.97972261e-17 2.12379484e-01 2.61335622e-15 3.14945084e-02\n",
      " 3.03829356e-01 1.61031790e-02 7.69550816e-02 4.38016891e-17\n",
      " 3.31995685e-22 2.16302389e-02]\n",
      "\n",
      " ------- Iteration : 7  - acc: 90.35  - rec:0.9081735620585267 -------  \n",
      "    Best Ensemble Weights: \n",
      " [1.84469574e-02 1.68200166e-03 2.44116730e-03 4.90274652e-01\n",
      " 2.34610850e-17 1.31757753e-05 4.99589674e-04 5.64739681e-02\n",
      " 1.12353829e-17 3.44082431e-02 7.71330722e-04 3.61273990e-03\n",
      " 3.91375287e-01 8.87697812e-07]\n",
      "\n",
      " ------- Iteration : 8  - acc: 89.9  - rec:0.9031281533804238 -------  \n",
      "    Best Ensemble Weights: \n",
      " [1.68804590e-01 1.77021038e-01 4.76524431e-01 1.46536541e-01\n",
      " 1.89329775e-16 1.56046156e-18 1.50155139e-02 2.85694784e-17\n",
      " 2.12956384e-17 1.50066095e-02 1.46837385e-17 1.09127728e-03\n",
      " 1.65690176e-19 1.18211225e-16]\n",
      "\n",
      " ------- Iteration : 9  - acc: 89.8  - rec:0.9061553985872856 -------  \n",
      "    Best Ensemble Weights: \n",
      " [7.01601894e-02 4.34742796e-02 1.66431444e-02 3.06925452e-01\n",
      " 2.00574332e-02 3.21676839e-01 5.68022705e-06 4.33530650e-02\n",
      " 1.53797515e-04 2.68610906e-02 1.46139592e-01 1.73669057e-03\n",
      " 2.81274761e-03 3.03719325e-19]\n",
      "\n",
      " ------- Iteration : 10  - acc: 89.9  - rec:0.9112008072653885 -------  \n",
      "    Best Ensemble Weights: \n",
      " [6.57127546e-02 6.59005782e-02 9.86951072e-02 1.04519007e-03\n",
      " 1.20798505e-03 4.15240010e-02 1.54765229e-02 1.22161775e-01\n",
      " 4.32252420e-01 1.00569250e-03 5.83198902e-03 3.04940672e-04\n",
      " 1.48430308e-01 4.50735237e-04]\n",
      "\n",
      " ------- Iteration : 11  - acc: 90.10000000000001  - rec:0.9142280524722503 -------  \n",
      "    Best Ensemble Weights: \n",
      " [1.74294921e-01 4.85943427e-02 8.58480048e-02 1.97097544e-02\n",
      " 1.52074018e-03 2.56578996e-01 2.49147220e-17 1.41630735e-18\n",
      " 2.22025042e-01 1.81416542e-03 1.02911704e-01 4.87277163e-04\n",
      " 8.62150529e-02 5.10807515e-17]\n",
      "\n",
      " ------- Iteration : 12  - acc: 89.45  - rec:0.9011099899091827 -------  \n",
      "    Best Ensemble Weights: \n",
      " [3.98840792e-01 1.76324021e-01 9.88645366e-18 3.46735814e-17\n",
      " 3.71645392e-02 1.29188841e-08 3.51954958e-17 3.76065960e-02\n",
      " 1.01306324e-17 2.49090102e-03 1.07653259e-17 1.27892302e-04\n",
      " 3.47445246e-01 4.16850892e-18]\n",
      "\n",
      " ------- Iteration : 13  - acc: 89.95  - rec:0.9132189707366297 -------  \n",
      "    Best Ensemble Weights: \n",
      " [8.18313534e-02 6.94073790e-02 1.82319523e-01 0.00000000e+00\n",
      " 6.42684882e-06 2.53779891e-01 4.03278803e-16 5.93026456e-02\n",
      " 2.40217968e-01 1.46750218e-03 1.11667235e-01 7.62924081e-08\n",
      " 3.81585505e-17 0.00000000e+00]\n",
      "\n",
      " ------- Iteration : 14  - acc: 90.05  - rec:0.9112008072653885 -------  \n",
      "    Best Ensemble Weights: \n",
      " [7.78244873e-03 1.68916836e-01 4.10123158e-02 4.08639562e-05\n",
      " 2.11457768e-02 1.50642771e-06 5.20333772e-06 1.22435444e-01\n",
      " 6.38276350e-01 4.67102356e-17 0.00000000e+00 3.83254002e-04\n",
      " 4.57303190e-17 2.44906448e-16]\n",
      "\n",
      " ------- Iteration : 15  - acc: 89.64999999999999  - rec:0.8950554994954592 -------  \n",
      "    Best Ensemble Weights: \n",
      " [1.71562373e-01 3.14679452e-01 1.61961413e-01 4.78032823e-05\n",
      " 1.09226286e-16 1.43067423e-01 2.04992194e-01 2.79840688e-17\n",
      " 5.53906356e-17 3.29499897e-03 1.56226268e-06 3.92779805e-04\n",
      " 4.56233457e-20 3.35533595e-18]\n",
      "\n",
      " ------- Iteration : 16  - acc: 89.3  - rec:0.900100908173562 -------  \n",
      "    Best Ensemble Weights: \n",
      " [7.01943118e-01 2.71280695e-08 2.95731677e-01 1.95699185e-05\n",
      " 4.43894471e-05 5.87668531e-09 4.88517530e-08 3.53365770e-18\n",
      " 8.52413045e-18 2.08971306e-03 2.25116884e-17 9.17743214e-05\n",
      " 2.40984820e-08 7.96522069e-05]\n",
      "\n",
      " ------- Iteration : 17  - acc: 89.55  - rec:0.9101917255297679 -------  \n",
      "    Best Ensemble Weights: \n",
      " [8.64481579e-02 3.64577793e-02 7.44030237e-03 6.22230663e-08\n",
      " 1.25771838e-02 2.67401342e-01 1.26403480e-01 3.47136432e-01\n",
      " 1.13823745e-01 3.45961855e-08 2.73541791e-08 4.08587233e-04\n",
      " 4.82204190e-19 1.90286626e-03]\n",
      "\n",
      " ------- Iteration : 18  - acc: 83.25  - rec:0.8446014127144299 -------  \n",
      "    Best Ensemble Weights: \n",
      " [3.70367195e-03 1.25113054e-05 2.45371292e-02 1.05926835e-01\n",
      " 2.64680528e-06 5.16766696e-02 5.52868168e-02 7.35782860e-01\n",
      " 1.24359478e-03 5.19193298e-03 1.37813841e-02 6.38294757e-04\n",
      " 2.21565284e-03 7.53502843e-20]\n",
      "\n",
      " ------- Iteration : 19  - acc: 89.85  - rec:0.900100908173562 -------  \n",
      "    Best Ensemble Weights: \n",
      " [2.46177911e-07 1.62681712e-01 6.05710280e-02 5.08921730e-02\n",
      " 6.37752924e-03 9.82068539e-02 3.06249503e-01 2.46151909e-02\n",
      " 1.35584646e-02 5.28480292e-03 2.70595276e-01 9.67220100e-04\n",
      " 5.07887758e-18 0.00000000e+00]\n",
      "\n",
      " ------- Iteration : 20  - acc: 90.3  - rec:0.9081735620585267 -------  \n",
      "    Best Ensemble Weights: \n",
      " [8.03554156e-02 5.00735280e-02 1.43064756e-01 2.30654987e-01\n",
      " 9.14717489e-04 7.64763743e-02 2.06434400e-02 9.98970573e-05\n",
      " 7.89935829e-02 1.84576633e-02 6.45011449e-02 1.07105188e-03\n",
      " 2.34693441e-01 1.49762148e-16]\n"
     ]
    }
   ],
   "source": [
    "# 模型集成：附权重\n",
    "best_acc,best_weights = MinimiseOptimize(preds,models_filenames,nb_classes,sample_N,testY,NUM_TESTS = 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best Accuracy :  90.4\n",
      "Best Weights :  [1.57919854e-02 2.25437178e-02 1.60078948e-01 1.37993631e-01\n",
      " 1.60363024e-03 1.91105368e-01 2.34578651e-02 1.24696769e-02\n",
      " 3.18793907e-03 1.29753377e-02 1.12151337e-01 7.62845967e-04\n",
      " 3.05643629e-01 2.34089531e-04]\n",
      "Accuracy :  90.4\n",
      "Recall :  0.9112008072653885\n"
     ]
    }
   ],
   "source": [
    "# 附权重的最终结果展示\n",
    "print(\"Best Accuracy : \", best_acc)\n",
    "print(\"Best Weights : \", best_weights)\n",
    "calculate_weighted_accuracy(best_weights)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
